techniques would be productive. In the ideal world, an obvious next step would be to update the parameters of the model based on more recent SDR data (1993). Unfortunately, this will not be possible because of radical changes that were made in the 1993 survey instrument, creating problems for comparisons with earlier years, although work is under way to assess the extent to which this lack of comparability presents problems.
Despite this barrier, efforts to refine the taxonomy, improve the estimation of immigration, and deal more adequately with the estimation of reentrants to the workforce can be expected to improve the performance of these models. Finally, the sensitivity of the estimated transitions to differences in gender needs to be explored.
In addition, efforts to expand the model ought to be undertaken. In particular, the effects of market feedback on the transition rates ought to be incorporated into the model. Both an assessment of the feasibility of transforming the transition estimates from parameters to functions that relate them to indicators of market conditions and efforts to expand the sensitivity of model outcomes to alternative market scenarios and variables need to be undertaken.
Life-table estimates can inform science policy by exploring the implications of very different rates of change in variables of interest (e.g. net migration, Ph.D. production, R&D funding), but they can only give a very rough estimate, especially if the data on which they are based are problematic or lack comparability over time. They are, however, one useful approach to the construction of estimates of future need for biomedical research personnel.